The technology described in this document can be embodied in a method that includes obtaining, by one or more image acquisition devices, a first image of a portion of a human body under illumination by electromagnetic radiation in a first wavelength range, and obtaining a second image of the portion of the human body under illumination by electromagnetic radiation in a second wavelength range. The method also includes generating, by one or more processing devices, a third image or template that combines information from the first image with information from the second image. The method also includes determining that one or more metrics representing a similarity between the third image and a template satisfy a threshold condition, and responsive to determining that the one or more metrics satisfy a threshold condition, providing access to the secure system.

A driver availability detection device includes an information acquisition unit to acquire information related to an occupant and a threshold setting unit to set an abnormal-state determination threshold for estimating the abnormal state of the occupant on a basis of an abnormal state score obtained by inputting the information related to the occupant acquired by the information acquisition unit to a machine learning model within a first threshold setting time.

A safe for the storage of a valuable, such as a firearm. The safe has an imaging system that is used to scan a portion of a human in the near infrared spectrum to image blood vessels and determine if the image matches a stored image and thereafter effect unlocking of the safe. A manual override lock system is provided to manually effect unlocking of the safe.

A method for extracting a major vessel region from a vessel image by a processor may comprise the steps of: extracting an entire vessel region from a vessel image; extracting a major vessel region from the vessel image on the basis of a machine learning model which extracts a major vessel region; and revising the major vessel region by connecting separated vessel portions on the basis of the entire vessel region.

A method for controlling access of users to desktops, comprising: 1. a user enters a login; 2. an organization server verifies if the user is authorized to access the desktop, and returns a pseudo of the user; 3. the user scans a pattern of fingerveins of one finger with a biometric scanner comprising cameras at different angles; 4. a file corresponding to said images is encrypted by said biometric scanner (B) with a public key of a biometric server and signed with a private key of said biometric scanner, and sent to the desktop; 5. the desktop forwards said file to said biometric server; 6. the biometric server decrypts the file, verifies the signature of the biometric scanner, and matches the received images with reference images associated with said pseudo; 7. the biometric server decides if the recognition succeeded, failed, or if an additional scan is needed.

The present disclosure relates to systems and methods for object recognition. The systems may obtain image data captured by an imaging device. The image data may include one or more objects. The systems may determine a centerline of a target object in the one or more objects based on the image data. The systems may determine a recognition result of the target object using a trained neural network model based on at least one feature parameter of the centerline of the target object. The recognition result may include a name of the target object. The systems may perform an anomaly detection on the target object based on the recognition result of the target object.

The present disclosure relates to systems and methods for object recognition. The systems may obtain image data captured by an imaging device. The image data may include one or more objects. The systems may determine a centerline of a target object in the one or more objects based on the image data. The systems may determine a recognition result of the target object using a trained neural network model based on at least one feature parameter of the centerline of the target object. The recognition result may include a name of the target object. The systems may perform an anomaly detection on the target object based on the recognition result of the target object.

An authentication method implemented by a computer, the authentication method including: extracting a feature amount of each of a plurality of feature points of a living body from imaged data of the living body; calculating a similarity between the feature amount of each of the plurality of feature points and a feature amount stored in a storage unit in association with a feature point that corresponds to each of the plurality of feature points; referring to the storage unit that stores weight information that indicates a weight to be applied to a similarity in association with the similarity to acquire the weight information associated with the calculated similarity; and executing authentication processing on the living body based on a similarity that is newly generated by applying the acquired weight information to the calculated similarity.

Methods, systems, and programming for identifying a person are presented. In one example, a first set of candidates is determined based on a fingerprint image acquired from a finger of the person. A second set of candidates is determined based on a finger vein image acquired from the finger. The person is recognized based on the first and/or second set of candidates.

The present disclosure provides a method for performing identity recognition on a to-be-recognized object, an electronic device, and a non-transitory computer-readable storage medium. The method includes: acquiring, by the infrared camera, and in response to an infrared camera turn-on condition being met, a first image of a to-be-recognized target, and performing target detection on the first image, the to-be-recognized target being a finger and/or a palm; acquiring, by the visible light camera, and in response to a visible light camera turn-on condition being met, a second image of the to-be-recognized target, and performing identifier code recognition on the second image; performing, in response to the to-be-recognized target being detected from the first image, identity recognition based on a third image, and determining an identity recognition result of the to-be-recognized object, the third image being at least one image among the first image in which the to-be-recognized target is detected.